AI 资讯
Vector Search in Elasticsearch: From Keywords to Meaning - Building Semantic Search and RAG Pipelines
You type "k8s deployment troubleshooting" into your documentation search. The top result is a page about Kubernetes architecture that never mentions the word "troubleshooting." It is exactly what you need. BM25 would have missed it entirely. This is the promise of vector search: finding documents by meaning, not just matching words. In 2025 and 2026, vector search has moved from niche ML engineering to a core Elasticsearch capability. If you are building search for AI applications - RAG pipelines, semantic Q&A, recommendation systems - understanding how Elasticsearch handles vectors is no longer optional. I have spent the past year building RAG pipelines at Cloudera, and I have learned that vector search is powerful but easy to misuse. This post covers what works, what does not, and how to implement it in production. Why Vector Search Matters (And When It Does Not) BM25, which we covered in a previous post, is brilliant at matching exact terms. But it is fundamentally lexical. It does not understand that: "k8s" and "kubernetes" are the same thing "docker container" and "containerization" are related concepts "out of memory error" and "heap exhaustion" describe the same problem Vector search solves this by converting text into high-dimensional numerical vectors (embeddings) where semantically similar content lives close together in vector space. A query for "k8s deployment troubleshooting" gets embedded into a vector, and Elasticsearch finds the nearest document vectors - even if they do not share a single keyword. But vector search is not a replacement for BM25. It is a complement. BM25 is faster, requires no ML infrastructure, and excels at exact-term matching. Vector search is slower, requires embedding models, and shines at conceptual similarity. The best search systems in 2026 use both. How Elasticsearch Stores and Indexes Vectors Elasticsearch introduced the dense_vector field type in version 7.x and has dramatically improved it through 8.x and into 2026. Here
AI 资讯
I Built an Image Compressor That Runs 100% in the Browser
Most "compress your image" websites upload your photo to a server. You don't need one. The browser's own canvas can re-encode an image at any quality — I built a drag-and-drop compressor in about 30 lines , and your photo never leaves your machine. 🗜️ Try it (drop a photo): https://dev48v.infy.uk/solve/day9-image-compressor.html 1. Catch the dropped file — locally drop . addEventListener ( " drop " , e => { e . preventDefault (); const file = e . dataTransfer . files [ 0 ]; // stays in the tab, 0 bytes uploaded loadImage ( file ); }); For sensitive images (IDs, screenshots), "never uploaded" is a real feature, not just a nicety. 2. Decode it into an <img> A dropped file is just bytes. Load it via a local blob: URL: const img = new Image (); img . src = URL . createObjectURL ( file ); await img . decode (); 3. Draw it onto a canvas Now the browser holds the raw pixels, detached from the original file format: canvas . width = img . naturalWidth ; canvas . height = img . naturalHeight ; canvas . getContext ( " 2d " ). drawImage ( img , 0 , 0 ); 4. Re-encode at a quality (this IS the compression) canvas . toBlob ( blob => { preview . src = URL . createObjectURL ( blob ); showSize ( blob . size ); }, " image/jpeg " , 0.7 ); // 0.7 = 70% quality JPEG and WebP are lossy — they discard detail the eye barely notices. That third argument is the entire compression dial; a small quality drop often halves the file size. 5. Hand the result back as a download link . href = URL . createObjectURL ( blob ); link . download = " compressed.jpg " ; // the browser saves it, no server The takeaway FileReader → Image → Canvas → toBlob is a surprisingly powerful local image pipeline. The same four steps do resizing, format conversion, cropping, watermarking — all client-side, all private. A whole category of "image tools" needs no backend at all. Open it and drop a photo.
AI 资讯
How to Rewrite a Chinese-Tenured Faculty Role for US Data Scientist Jobs
Why Your Chinese-Tenured Faculty Resume Won’t Work in US Industry US data scientist hiring managers scan a resume in 7–15 seconds looking for one thing: evidence you can solve business problems with data. A Chinese faculty resume often leads with tenure status, publication counts, and grant amounts—none of which translate to industry value. Worse, the CV-style length and Chinese-specific qualifications (e.g., “Professor of Record,” “National Natural Science Foundation PI”) confuse HR software and recruiters unfamiliar with that system. You need to strip the academic frame and rebuild around what a US data scientist does: clean messy data, build predictive models, deploy to production, and communicate results to non-technical stakeholders. Think of every faculty achievement as raw material you must reframe. Core Rewriting Rules: From Academic to Industry Rule 1: Replace Tenure Rank with a US-Equivalent Data Science Title Do not list “Tenured Associate Professor” unless it is your most recent position at a well-known university (e.g., Peking University, Tsinghua). Instead, use a title that reveals your function: “Senior Data Scientist – Research Computing” or “Lead Data Scientist – Machine Learning Research Lab.” The point is to signal the job function, not the academic rank. Example: Before: “Tenured Associate Professor, School of Computer Science, Fudan University” After: “Senior Data Scientist / Research Lead, Fudan University AI Lab” Rule 2: Translate Every Accomplishment into a Business-Relevant Metric Chinese faculty resumes often say “published 15 papers in top-tier journals” or “secured ¥3M in research funding.” That means nothing to a hiring manager at a fintech startup. Instead, describe what you did with the data and the outcome. Concrete example – before and after: BEFORE (faculty bullet): “Led research project on deep learning for medical image segmentation; published 3 papers in IEEE TMI.” AFTER (industry data scientist bullet): “Built and validated a co
AI 资讯
Ngrx Signal Store
In recent years, Angular has taken an important step toward a simpler and more declarative reactivity model with the introduction of Signals . NgRx, which has long been the de facto standard for state management in complex Angular applications, followed this evolution by introducing Signal Store . The goal is not to completely replace @ngrx/store , but to offer a lighter and more local alternative, designed for use cases where the classic Actions → Reducers → Selectors pattern feels excessive. In this article, we'll see how to use NgRx Signal Store to build a reactive, typed store that integrates seamlessly with Angular components, drastically reducing boilerplate and improving code readability. This tutorial is aimed at Angular developers who are already familiar with Signals and "classic" NgRx. What is NgRx Signal Store NgRx Signal Store introduces a different way of thinking about state compared to classic @ngrx/store . A Signal Store : is not based on Redux does not use actions or reducers does not require explicit selectors Instead, the model revolves around three main concepts: 🧩 State State is defined as a set of signals , typically using withState . Each state property is immediately reactive and can be read directly by components. 🧠 Derived state Derived state is defined using withComputed . It is the conceptual equivalent of selectors, but with a more direct syntax and better integration with Angular's Signals system. 🔧 Methods State changes and side effects (such as HTTP calls) are encapsulated in methods declared with withMethods . This keeps the store logic in a single place, without having to orchestrate multiple files as in the traditional NgRx pattern. In other words, a Signal Store resembles a strongly structured reactive service more than a pure Redux store. This approach makes Signal Stores particularly suitable for: local or feature state small to medium-sized applications reducing complexity in contexts where Redux would be overkill Creating the
AI 资讯
SanDisk’s new PlayStation 5 SSD will cost you more than three PS5 Pros
SanDisk has announced an expensive way to boost the PlayStation 5's storage capacity. The company's new Optimus GX PRO 850P NVMe SSD is an officially licensed PS5 accessory in capacities ranging from 1TB to 8TB. The largest option can store up to 200 PS5 games (based on average installation sizes) SanDisk claims, but thanks to […]
AI 资讯
The Siren Song of ariaNotify()
There's a brand new ariaNotify() method — defined by the WAI-ARIA 1.3 Specification — that provides a means of programmatically triggering narration in a screen reader. The Siren Song of ariaNotify() originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.
创业投融资
The slowtech revolution is here to kill your phone addiction and rescue your attention span
“People just really want to take back control of their time, their lives, their attention... They’re down for whatever helps them do that.”
科技前沿
"Truly evil" FDA rejection of gene therapy overturned after Trump official ousted
Gene therapy company UniQure had another FDA meeting after Vinay Prasad's exit.
AI 资讯
Collecting robot training data is dirty, unglamorous work. Some AI labs are already paying XDOF to do it.
If physical AI is going to match the accomplishments of LLMs, there's a data problem that needs to be solved.
开发者
Lego unveils its first working pinball machine
Lego's newest set is a fully functional miniature pinball machine.
AI 资讯
Paramount Plus is two dollars for two months of ad-free viewing
Paramount Plus is offering new and former subscribers a discounted rate until June 25th, 2026. You’ll pay 99 cents per month for the first two months, with the Premium plan automatically renewing for $13.99 per month after that, and the more limited Essential plan renewing for $8.99. Both plans include some excellent shows, like Freaks […]
AI 资讯
In a big year for horror, Widow’s Bay still stands apart
Horror is having a moment. In 2026, the genre is especially well-represented: new blood is dominating the box office through films like Backrooms and Obsession, established names like Sam Raimi and Damian McCarthy are at the top of their game, and long-running franchises like 28 Years Later and Resident Evil continue to stay relevant. But […]
AI 资讯
Pramaana Labs raises $27M seed round from Khosla Ventures to bring formal verification to AI
Pramaana will focus on highly sensitive verticals like law, drug discovery, and tax preparation — where errors can be costly and reliability is at a premium.
AI 资讯
How to find the best deals during Amazon’s Prime Day sale
Amazon’s Prime Day is one of the biggest shopping events of the year, and the four-day sale for 2026 begins June 23rd at 3:01AM ET and ends at the same time on June 27th. It will grant Prime members access to some of the best prices of the year on Amazon devices, as well as […]
开发者
In Toy Story 5, the problem really is these damn phones (and tablets)
The Toy Story franchise began with a story about a vintage doll feeling threatened by the arrival of an electronic action figure. Woody and Buzz's rivalry embodied a shift that was happening in the '90s as children's toys were becoming more technologically sophisticated, and while toys have gotten even more tech-focused in the years since, […]
产品设计
Propane
Automatic customer context for product teams and agents. Discussion | Link
AI 资讯
AI search grounded in Facebook posts? What could go wrong?
AI is pretty reliable at putting things on your calendar these days, but it hasn't quite cracked answering the related and all-important question of "What should I do this weekend?" Meta's new AI Mode in search could be a useful tool - if it ever learns to stop getting stuff wrong. AI Mode is a […]
产品设计
SpaceX alum nabs $22M to turn rocket engines into geothermal power plants
Critical Energy is turning rocket engines into geothermal power plants, and it wants to build 300 GW per year by 2045.
科技前沿
How to stop Netflix from asking 'are you still watching?'
If you've been feeling shamed or annoyed by the question popping up during your binge-watching sessions, here's how to turn off the feature.
AI 资讯
The best Apple deals you can already get ahead of Prime Day
Amazon’s Prime Day sale kicks off on June 23rd, but already we’re seeing some notable Apple deals trickle in. Whether you’re looking for a new pair of wireless earbuds or a smartwatch, many retailers are offering notable discounts ahead of the shopping event. Walmart and Amazon recently surprised us with a new all-time low on […]